code: def init(self, num_embeddings, embedding_dim, op_func):
      self.inputs = {
          "weight": torch.rand(
              num_embeddings, embedding_dim, dtype=torch.float
          )
          + 1
      }
      self.op_func = op_func
  
file_path: pytorch/benchmarks/operator_benchmark/pt/qembedding_pack_test.py
imports: import torch
  import operator_benchmark
label_desc: Use image node_id 1 for calling the EmbeddingBagFloatToFusedBase obj's underlying member method code with example usage: obj.init(num_embeddings, embedding_dim, op_func) without return types